disfluency-large – AI Model by DD0101 | AlphaNeural AI

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DD0101/
disfluency-large

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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disfluency-large

This model is a fine-tuned version of vinai/phobert-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0438
Precision: 0.9698
Recall: 0.9663
F1: 0.9681
Accuracy: 0.9921

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	140	0.0422	0.9651	0.9627	0.9639	0.9902
No log	2.0	280	0.0315	0.9718	0.9730	0.9724	0.9923
No log	3.0	420	0.2221	0.8079	0.7530	0.7795	0.9355
0.024	4.0	560	0.0379	0.9693	0.9675	0.9684	0.9926
0.024	5.0	700	0.0499	0.9657	0.9639	0.9648	0.9905
0.024	6.0	840	0.0388	0.9688	0.9688	0.9688	0.9925
0.024	7.0	980	0.0438	0.9698	0.9663	0.9681	0.9921

Framework versions

Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3